In [34]:
import pandas as pd
import numpy as np
import csv
!pip install gensim
from gensim import corpora, models
from gensim.models import CoherenceModel
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
import nltk
nltk.download('stopwords')
import nltk
nltk.download('punkt')
import nltk
nltk.download('wordnet')
nltk.download('omw-1.4')
!pip install pyLDAvis
import gensim
from gensim.models import LdaModel
from gensim.corpora import Dictionary
from gensim.models.coherencemodel import CoherenceModel


# Replace 'path/to/your/data.csv' with your actual data file path
#data_path = '/content/Reviews Virtual .csv'
df = pd.read_csv("Final Dataset.csv")

# Select the column containing reviews
reviews = df['Column 1']

# Remove stopwords
stop_words = stopwords.words('english')
processed_reviews = []
for review in reviews:
  processed_review = [word for word in word_tokenize(review.lower()) if word not in stop_words]
  processed_reviews.append(processed_review)

# Remove punctuation and numbers
import string
processed_reviews_clean = []
for review in processed_reviews:
  processed_review_clean = [word for word in review if word not in string.punctuation and not word.isdigit()]
  processed_reviews_clean.append(processed_review_clean)

# Lemmatize words (optional)
from nltk.stem import WordNetLemmatizer
lemmatizer = WordNetLemmatizer()
processed_reviews_lemmatized = []
for review in processed_reviews_clean:
  processed_review_lemmatized = [lemmatizer.lemmatize(word) for word in review]
  processed_reviews_lemmatized.append(processed_review_lemmatized)

# Choose processed data based on your preference (stopwords removed, stopwords + punctuation/numbers removed, or lemmatized)
processed_reviews = processed_reviews_clean # Replace with desired data

# Create dictionary
dictionary = corpora.Dictionary(processed_reviews)

# Create corpus
corpus = [dictionary.doc2bow(review) for review in processed_reviews]

topic_klrd_dict = {}
coherence_score_set = []
for num_topics in range(3, 61):

    if num_topics==3 or num_topics ==4 or num_topics==5 or num_topics==6 or num_topics==12:
        # Train LDA model
        lda_model = models.LdaModel(corpus, id2word=dictionary, num_topics=num_topics)
        
        def regularized_kl_divergence(lda_model, prior_distribution, alpha):
          # Calculate KL divergence for each topic
          kl_divergence = np.zeros(lda_model.num_topics)
          for doc_topic_dist in lda_model[corpus]:  # Iterate through document topic distributions
            for topic_id, topic_prob in doc_topic_dist:
              kl_divergence[topic_id] += topic_prob * np.log(topic_prob / prior_distribution[topic_id])
        
          # Normalise by the number of documents
          kl_divergence /= len(corpus)
        
          # Regularize with a hyperparameter (alpha)
          regularization = alpha * np.sum(np.square(prior_distribution))
        
          return np.mean(kl_divergence) + regularization
        
        # Define your prior distribution (e.g., uniform distribution)
        prior_distribution = np.ones(lda_model.num_topics) / lda_model.num_topics
        
        # Choose a hyperparameter alpha for regularization
        alpha = 0.05
    
        # Calculate regularized KL divergence
        reg_kl_div = regularized_kl_divergence(lda_model, prior_distribution, alpha)
        
        print("Number of Topics:", num_topics)

        for topic_id in range(num_topics):
          print(f"Topic {topic_id + 1}:", lda_model.print_topic(topic_id, topn=50))
        
        print("Regularized KL Divergence:", reg_kl_div)
    
        import re
    
        # Tokenize and clean the reviews
        unicode_reviews = [
            re.sub(r'[^\x00-\x7F]+', '', review).split()
            for review in df['Column 1'].tolist()
        ]
        
        # Compute Coherence Score
        coherence_model_lda = CoherenceModel(model=lda_model, texts=unicode_reviews, corpus=processed_reviews, coherence='u_mass')
        coherence_lda = coherence_model_lda.get_coherence()
        print('\nCoherence Score: ', coherence_lda)
        coherence_score_set.append(coherence_lda)
    
        topic_klrd_dict[num_topics]=[(reg_kl_div, coherence_lda)]

        from wordcloud import WordCloud
        import matplotlib.pyplot as plt
        
        # Function to generate and display wordcloud for a specific topic
        def generate_wordcloud(topic, lda_model, dictionary, stop_words):
          # Get topic words and probabilities
          topic_words = lda_model.show_topic(topic, topn=20)  # Adjust topn as needed
          word_probs = {word: prob for word, prob in topic_words}
        
          # Remove stopwords before feeding to WordCloud
          filtered_word_probs = {word: prob for word, prob in word_probs.items() if word not in stop_words}
        
          # Create and display WordCloud
          wordcloud = WordCloud(width=800, height=600, background_color="white").generate_from_frequencies(filtered_word_probs)
          plt.figure(figsize=(8, 6))
          plt.imshow(wordcloud, interpolation="bilinear")
          plt.axis("off")
          plt.title(f"Topic {topic + 1} Word Cloud")
          plt.show()

        # Generate wordcloud for each topic
        stop_words = stopwords.words('english')
        for topic in range(num_topics):
          generate_wordcloud(topic, lda_model, dictionary, stop_words)

    else:
       # Train LDA model
        lda_model = models.LdaModel(corpus, id2word=dictionary, num_topics=num_topics)
        
        def regularized_kl_divergence(lda_model, prior_distribution, alpha):
          # Calculate KL divergence for each topic
          kl_divergence = np.zeros(lda_model.num_topics)
          for doc_topic_dist in lda_model[corpus]:  # Iterate through document topic distributions
            for topic_id, topic_prob in doc_topic_dist:
              kl_divergence[topic_id] += topic_prob * np.log(topic_prob / prior_distribution[topic_id])
        
          # Normalise by the number of documents
          kl_divergence /= len(corpus)
        
          # Regularize with a hyperparameter (alpha)
          regularization = alpha * np.sum(np.square(prior_distribution))
        
          return np.mean(kl_divergence) + regularization
        
        # Define your prior distribution (e.g., uniform distribution)
        prior_distribution = np.ones(lda_model.num_topics) / lda_model.num_topics
        
        # Choose a hyperparameter alpha for regularization
        alpha = 0.05
    
        # Calculate regularized KL divergence
        reg_kl_div = regularized_kl_divergence(lda_model, prior_distribution, alpha) 

        print("Number of Topics:", num_topics)
        print("Regularized KL Divergence:", reg_kl_div)
    
        import re
    
        # Tokenize and clean the reviews
        unicode_reviews = [
            re.sub(r'[^\x00-\x7F]+', '', review).split()
            for review in df['Column 1'].tolist()
        ]
        
        # Compute Coherence Score
        coherence_model_lda = CoherenceModel(model=lda_model, texts=unicode_reviews, corpus=processed_reviews, coherence='u_mass')
        coherence_lda = coherence_model_lda.get_coherence()
        print('\nCoherence Score: ', coherence_lda)
        if coherence_lda>max(coherence_score_set):
            for topic_id in range(num_topics):
              print(f"Topic {topic_id + 1}:", lda_model.print_topic(topic_id, topn=50))
            # Function to generate and display wordcloud for a specific topic
            def generate_wordcloud(topic, lda_model, dictionary, stop_words):
              # Get topic words and probabilities
              topic_words = lda_model.show_topic(topic, topn=20)  # Adjust topn as needed
              word_probs = {word: prob for word, prob in topic_words}
            
              # Remove stopwords before feeding to WordCloud
              filtered_word_probs = {word: prob for word, prob in word_probs.items() if word not in stop_words}
            
              # Create and display WordCloud
              wordcloud = WordCloud(width=800, height=600, background_color="white").generate_from_frequencies(filtered_word_probs)
              plt.figure(figsize=(8, 6))
              plt.imshow(wordcloud, interpolation="bilinear")
              plt.axis("off")
              plt.title(f"Topic {topic + 1} Word Cloud")
              plt.show()

            # Generate wordcloud for each topic
            stop_words = stopwords.words('english')
            for topic in range(num_topics):
              generate_wordcloud(topic, lda_model, dictionary, stop_words)
        coherence_score_set.append(coherence_lda)
        topic_klrd_dict[num_topics]=[(reg_kl_div, coherence_lda)]


# Specify the desired CSV file name
csv_file = "Final_RD_Coherence.csv"

# Open the CSV file in write mode
with open(csv_file, "w", newline="") as csvfile:
    # Create a CSV writer object
    csv_writer = csv.writer(csvfile)

    # Write the dictionary keys as the first row (header)
    csv_writer.writerow(topic_klrd_dict.keys())

    # Write the values of the dictionary as rows
    csv_writer.writerow(topic_klrd_dict.values())

print("Dictionary successfully converted to CSV file:", csv_file)
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Number of Topics: 3
Topic 1: 0.032*"experience" + 0.027*"great" + 0.016*"fun" + 0.015*"recommend" + 0.013*"made" + 0.013*"class" + 0.012*"really" + 0.012*"highly" + 0.011*"us" + 0.010*"interesting" + 0.008*"art" + 0.008*"lot" + 0.007*"host" + 0.007*"feel" + 0.007*"wonderful" + 0.007*"amazing" + 0.007*"way" + 0.007*"friendly" + 0.007*"’" + 0.007*"reading" + 0.007*"learned" + 0.006*"time" + 0.006*"easy" + 0.006*"learn" + 0.006*"make" + 0.006*"history" + 0.006*"engaging" + 0.006*"would" + 0.006*"also" + 0.006*"stories" + 0.005*"session" + 0.005*"learning" + 0.005*"knowledgeable" + 0.005*"well" + 0.005*"accurate" + 0.005*"making" + 0.005*"good" + 0.005*"loved" + 0.005*"cooking" + 0.005*"job" + 0.005*"excellent" + 0.004*"everyone" + 0.004*"new" + 0.004*"super" + 0.004*"things" + 0.004*"recommended" + 0.004*"enjoyed" + 0.004*"even" + 0.004*"like" + 0.004*"culture"
Topic 2: 0.045*"experience" + 0.027*"recommend" + 0.027*"great" + 0.024*"fun" + 0.019*"time" + 0.019*"team" + 0.019*"would" + 0.016*"highly" + 0.011*"event" + 0.010*"virtual" + 0.010*"definitely" + 0.010*"really" + 0.009*"group" + 0.008*"host" + 0.008*"amazing" + 0.008*"chart" + 0.007*"much" + 0.007*"activity" + 0.007*"loved" + 0.007*"way" + 0.007*"work" + 0.007*"everyone" + 0.006*"wonderful" + 0.006*"’" + 0.006*"engaging" + 0.005*"first" + 0.005*"well" + 0.005*"us" + 0.005*"enjoyed" + 0.005*"booked" + 0.005*"together" + 0.005*"friends" + 0.005*"family" + 0.004*"fantastic" + 0.004*"anyone" + 0.004*"absolutely" + 0.004*"super" + 0.004*"made" + 0.004*"done" + 0.004*"astrology" + 0.003*"something" + 0.003*"one" + 0.003*"online" + 0.003*"lot" + 0.003*"good" + 0.003*"even" + 0.003*"reading" + 0.003*"different" + 0.003*"better" + 0.003*"thank"
Topic 3: 0.024*"tour" + 0.023*"experience" + 0.019*"sharon" + 0.014*"thank" + 0.013*"much" + 0.011*"mark" + 0.010*"enjoyed" + 0.010*"great" + 0.010*"really" + 0.009*"roberto" + 0.008*"us" + 0.008*"’" + 0.008*"time" + 0.008*"see" + 0.007*"questions" + 0.007*"life" + 0.007*"thanks" + 0.007*"prague" + 0.006*"like" + 0.006*"visit" + 0.006*"person" + 0.006*"wonderful" + 0.006*"guide" + 0.006*"ireland" + 0.006*"best" + 0.006*"city" + 0.005*"history" + 0.005*"knowledgeable" + 0.005*"one" + 0.005*"beautiful" + 0.005*"lovely" + 0.005*"also" + 0.004*"travel" + 0.004*"future" + 0.004*"david" + 0.004*"nice" + 0.004*"street" + 0.004*"delicious" + 0.004*"meditation" + 0.004*"day" + 0.004*"loved" + 0.004*"love" + 0.004*"knowledge" + 0.004*"interesting" + 0.004*"felt" + 0.004*"know" + 0.004*"lot" + 0.004*"ben" + 0.004*"plague" + 0.003*"well"
Regularized KL Divergence: 0.162779642773183

Coherence Score:  -4.962767259118948
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Number of Topics: 4
Topic 1: 0.049*"sharon" + 0.033*"thank" + 0.030*"mark" + 0.027*"much" + 0.025*"roberto" + 0.018*"enjoyed" + 0.018*"thanks" + 0.016*"experience" + 0.014*"see" + 0.014*"tour" + 0.013*"great" + 0.012*"best" + 0.011*"ben" + 0.010*"david" + 0.009*"time" + 0.008*"keshav" + 0.008*"tacos" + 0.008*"soon" + 0.008*"glad" + 0.008*"hope" + 0.008*"really" + 0.007*"happy" + 0.007*"lovely" + 0.007*"meditation" + 0.007*"trip" + 0.007*"im" + 0.007*"meeting" + 0.007*"prague" + 0.006*"future" + 0.006*"flor" + 0.006*"city" + 0.005*"meet" + 0.005*"visit" + 0.005*"nice" + 0.005*"forward" + 0.005*"pompeii" + 0.005*"know" + 0.005*"ireland" + 0.005*"day" + 0.005*"one" + 0.004*"kind" + 0.004*"person" + 0.004*"lot" + 0.004*"spot" + 0.004*"look" + 0.004*"review" + 0.004*"following" + 0.004*"plague" + 0.004*"joining" + 0.003*"wishes"
Topic 2: 0.038*"team" + 0.025*"great" + 0.020*"event" + 0.020*"experience" + 0.018*"fun" + 0.014*"work" + 0.012*"everyone" + 0.011*"virtual" + 0.010*"really" + 0.010*"activity" + 0.009*"session" + 0.009*"enjoyed" + 0.008*"us" + 0.008*"time" + 0.008*"booked" + 0.007*"group" + 0.006*"recommend" + 0.006*"highly" + 0.006*"building" + 0.006*"loved" + 0.006*"engaging" + 0.005*"making" + 0.005*"job" + 0.004*"well" + 0.004*"lot" + 0.004*"bonding" + 0.004*"amazing" + 0.004*"engaged" + 0.004*"people" + 0.004*"company" + 0.004*"tours" + 0.004*"way" + 0.003*"host" + 0.003*"events" + 0.003*"marks" + 0.003*"learning" + 0.003*"fantastic" + 0.003*"together" + 0.003*"even" + 0.003*"easy" + 0.003*"able" + 0.003*"private" + 0.003*"vedic" + 0.003*"japanese" + 0.003*"super" + 0.003*"perfect" + 0.003*"steps" + 0.003*"good" + 0.003*"much" + 0.003*"graciela"
Topic 3: 0.058*"experience" + 0.044*"great" + 0.040*"recommend" + 0.037*"fun" + 0.024*"highly" + 0.024*"would" + 0.018*"time" + 0.015*"host" + 0.014*"definitely" + 0.012*"really" + 0.012*"group" + 0.010*"engaging" + 0.010*"amazing" + 0.009*"family" + 0.009*"wonderful" + 0.009*"much" + 0.008*"david" + 0.008*"everyone" + 0.008*"way" + 0.007*"friends" + 0.007*"super" + 0.007*"beautiful" + 0.007*"made" + 0.007*"lot" + 0.007*"anyone" + 0.007*"loved" + 0.006*"well" + 0.006*"chart" + 0.006*"virtual" + 0.006*"activity" + 0.006*"learned" + 0.006*"interactive" + 0.006*"interesting" + 0.005*"enjoyed" + 0.005*"job" + 0.005*"fantastic" + 0.005*"italy" + 0.005*"together" + 0.005*"good" + 0.004*"energy" + 0.004*"us" + 0.004*"prague" + 0.004*"answered" + 0.004*"excellent" + 0.004*"questions" + 0.004*"informative" + 0.004*"friendly" + 0.004*"storyteller" + 0.003*"funny" + 0.003*"entertaining"
Topic 4: 0.030*"experience" + 0.014*"tour" + 0.013*"great" + 0.012*"’" + 0.012*"us" + 0.011*"really" + 0.009*"made" + 0.009*"time" + 0.008*"wonderful" + 0.008*"reading" + 0.008*"history" + 0.008*"class" + 0.007*"knowledgeable" + 0.007*"recommend" + 0.007*"interesting" + 0.007*"like" + 0.006*"questions" + 0.006*"life" + 0.006*"also" + 0.006*"highly" + 0.006*"feel" + 0.006*"fun" + 0.005*"loved" + 0.005*"make" + 0.005*"way" + 0.005*"amazing" + 0.005*"art" + 0.005*"learned" + 0.005*"friendly" + 0.005*"well" + 0.005*"felt" + 0.005*"lot" + 0.005*"astrology" + 0.005*"delicious" + 0.004*"stories" + 0.004*"would" + 0.004*"things" + 0.004*"even" + 0.004*"learn" + 0.004*"guide" + 0.004*"person" + 0.004*"new" + 0.004*"cooking" + 0.004*"one" + 0.004*"gave" + 0.004*"knowledge" + 0.004*"enjoyed" + 0.004*"culture" + 0.003*"accurate" + 0.003*"able"
Regularized KL Divergence: 0.16081339540669698

Coherence Score:  -4.4155824491468385
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Number of Topics: 5
Topic 1: 0.041*"sharon" + 0.025*"mark" + 0.023*"experience" + 0.023*"thank" + 0.020*"much" + 0.015*"enjoyed" + 0.014*"thanks" + 0.014*"great" + 0.012*"roberto" + 0.011*"see" + 0.010*"really" + 0.010*"best" + 0.010*"beautiful" + 0.010*"ben" + 0.008*"class" + 0.008*"session" + 0.008*"meditation" + 0.007*"time" + 0.007*"us" + 0.007*"also" + 0.007*"keshav" + 0.006*"glad" + 0.006*"street" + 0.006*"lot" + 0.006*"david" + 0.006*"lovely" + 0.006*"soon" + 0.005*"hope" + 0.005*"im" + 0.005*"meeting" + 0.005*"future" + 0.005*"questions" + 0.005*"happy" + 0.005*"forward" + 0.005*"one" + 0.005*"nice" + 0.005*"kind" + 0.004*"answered" + 0.004*"look" + 0.004*"person" + 0.004*"ireland" + 0.004*"reading" + 0.004*"tacos" + 0.004*"meet" + 0.004*"looking" + 0.004*"amazing" + 0.003*"wishes" + 0.003*"learned" + 0.003*"day" + 0.003*"review"
Topic 2: 0.023*"experience" + 0.019*"great" + 0.016*"time" + 0.015*"us" + 0.014*"way" + 0.009*"accurate" + 0.008*"fun" + 0.008*"questions" + 0.008*"feel" + 0.008*"friendly" + 0.007*"wonderful" + 0.007*"knowledgeable" + 0.007*"get" + 0.007*"interesting" + 0.007*"really" + 0.007*"gave" + 0.006*"like" + 0.006*"hour" + 0.006*"’" + 0.006*"history" + 0.006*"informative" + 0.005*"well" + 0.005*"ireland" + 0.005*"good" + 0.005*"made" + 0.005*"warm" + 0.005*"different" + 0.005*"insights" + 0.005*"able" + 0.005*"know" + 0.005*"learn" + 0.004*"host" + 0.004*"make" + 0.004*"prague" + 0.004*"italy" + 0.004*"information" + 0.004*"better" + 0.004*"things" + 0.004*"making" + 0.004*"fascinating" + 0.004*"excellent" + 0.004*"nice" + 0.004*"astrology" + 0.004*"ask" + 0.004*"even" + 0.004*"video" + 0.004*"people" + 0.004*"life" + 0.004*"spend" + 0.003*"much"
Topic 3: 0.058*"experience" + 0.048*"recommend" + 0.038*"great" + 0.035*"highly" + 0.027*"fun" + 0.025*"team" + 0.022*"would" + 0.016*"time" + 0.014*"event" + 0.012*"engaging" + 0.012*"host" + 0.011*"amazing" + 0.011*"everyone" + 0.011*"group" + 0.011*"virtual" + 0.010*"definitely" + 0.009*"loved" + 0.009*"activity" + 0.009*"wonderful" + 0.009*"really" + 0.008*"david" + 0.008*"work" + 0.008*"anyone" + 0.008*"family" + 0.007*"enjoyed" + 0.007*"knowledgeable" + 0.007*"fantastic" + 0.007*"recommended" + 0.007*"booked" + 0.006*"informative" + 0.006*"’" + 0.005*"interactive" + 0.005*"super" + 0.005*"friends" + 0.005*"much" + 0.005*"job" + 0.004*"excellent" + 0.004*"friendly" + 0.004*"engaged" + 0.004*"absolutely" + 0.004*"made" + 0.004*"lot" + 0.004*"well" + 0.004*"funny" + 0.004*"session" + 0.004*"class" + 0.004*"way" + 0.004*"building" + 0.003*"birthday" + 0.003*"storyteller"
Topic 4: 0.041*"tour" + 0.026*"experience" + 0.016*"’" + 0.015*"really" + 0.014*"reading" + 0.014*"history" + 0.013*"art" + 0.012*"delicious" + 0.011*"enjoyed" + 0.011*"wonderful" + 0.010*"life" + 0.010*"class" + 0.010*"chart" + 0.010*"learned" + 0.010*"great" + 0.010*"knowledge" + 0.009*"loved" + 0.008*"visit" + 0.008*"city" + 0.008*"like" + 0.008*"astrology" + 0.008*"learning" + 0.008*"us" + 0.007*"much" + 0.007*"stories" + 0.007*"culture" + 0.007*"new" + 0.007*"interesting" + 0.007*"prague" + 0.007*"amazing" + 0.007*"made" + 0.007*"guide" + 0.006*"thank" + 0.006*"wait" + 0.006*"love" + 0.005*"fun" + 0.005*"learn" + 0.005*"roberto" + 0.005*"person" + 0.005*"insightful" + 0.005*"also" + 0.005*"lot" + 0.005*"make" + 0.004*"drawing" + 0.004*"cant" + 0.004*"time" + 0.004*"plague" + 0.004*"felt" + 0.004*"things" + 0.004*"streets"
Topic 5: 0.034*"experience" + 0.023*"great" + 0.021*"fun" + 0.015*"made" + 0.013*"really" + 0.012*"cooking" + 0.011*"recommend" + 0.010*"us" + 0.010*"would" + 0.009*"time" + 0.009*"host" + 0.008*"definitely" + 0.008*"easy" + 0.008*"lot" + 0.007*"travel" + 0.007*"well" + 0.007*"sure" + 0.007*"’" + 0.007*"interesting" + 0.006*"amazing" + 0.006*"questions" + 0.006*"trip" + 0.006*"make" + 0.006*"virtual" + 0.006*"highly" + 0.005*"everything" + 0.005*"super" + 0.005*"good" + 0.005*"online" + 0.005*"like" + 0.005*"first" + 0.005*"way" + 0.004*"even" + 0.004*"felt" + 0.004*"also" + 0.004*"get" + 0.004*"explained" + 0.004*"follow" + 0.004*"things" + 0.004*"group" + 0.004*"could" + 0.004*"know" + 0.004*"different" + 0.004*"together" + 0.004*"one" + 0.004*"done" + 0.004*"everyone" + 0.004*"information" + 0.003*"never" + 0.003*"step"
Regularized KL Divergence: 0.1450421551884395

Coherence Score:  -4.235712309566841
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Number of Topics: 6
Topic 1: 0.068*"tour" + 0.015*"great" + 0.015*"guide" + 0.014*"time" + 0.014*"accurate" + 0.014*"well" + 0.012*"really" + 0.012*"us" + 0.010*"fun" + 0.010*"chart" + 0.009*"virtual" + 0.009*"questions" + 0.008*"prague" + 0.008*"experience" + 0.008*"city" + 0.008*"easy" + 0.007*"good" + 0.007*"travel" + 0.006*"follow" + 0.006*"walking" + 0.006*"india" + 0.006*"know" + 0.005*"instructions" + 0.005*"plague" + 0.005*"get" + 0.005*"also" + 0.005*"done" + 0.005*"interesting" + 0.004*"much" + 0.004*"sure" + 0.004*"’" + 0.004*"things" + 0.004*"mexico" + 0.004*"astrology" + 0.004*"clear" + 0.004*"job" + 0.004*"lot" + 0.004*"along" + 0.004*"enjoyed" + 0.004*"following" + 0.004*"way" + 0.004*"host" + 0.004*"like" + 0.004*"class" + 0.003*"wine" + 0.003*"could" + 0.003*"one" + 0.003*"helped" + 0.003*"specific" + 0.003*"able"
Topic 2: 0.022*"experience" + 0.015*"delicious" + 0.014*"visit" + 0.013*"’" + 0.012*"class" + 0.010*"street" + 0.010*"person" + 0.009*"one" + 0.009*"life" + 0.009*"great" + 0.009*"like" + 0.008*"make" + 0.008*"meditation" + 0.007*"nice" + 0.007*"time" + 0.007*"wonderful" + 0.007*"food" + 0.007*"future" + 0.007*"get" + 0.007*"us" + 0.007*"forward" + 0.006*"trip" + 0.006*"reading" + 0.006*"would" + 0.006*"take" + 0.006*"wait" + 0.006*"felt" + 0.005*"definitely" + 0.005*"love" + 0.005*"looking" + 0.005*"look" + 0.005*"amazing" + 0.005*"see" + 0.005*"first" + 0.005*"go" + 0.005*"able" + 0.005*"want" + 0.005*"really" + 0.004*"mark" + 0.004*"another" + 0.004*"also" + 0.004*"cant" + 0.004*"could" + 0.004*"loved" + 0.004*"made" + 0.004*"city" + 0.004*"day" + 0.004*"streets" + 0.004*"online" + 0.004*"learn"
Topic 3: 0.050*"great" + 0.048*"experience" + 0.040*"fun" + 0.037*"team" + 0.029*"recommend" + 0.021*"event" + 0.020*"highly" + 0.019*"time" + 0.016*"activity" + 0.016*"would" + 0.016*"beautiful" + 0.014*"group" + 0.013*"virtual" + 0.013*"work" + 0.012*"everyone" + 0.011*"way" + 0.010*"really" + 0.010*"host" + 0.010*"engaging" + 0.010*"family" + 0.009*"loved" + 0.009*"insightful" + 0.008*"definitely" + 0.008*"enjoyed" + 0.008*"wonderful" + 0.008*"amazing" + 0.008*"together" + 0.007*"much" + 0.007*"friends" + 0.007*"booked" + 0.007*"italy" + 0.006*"answered" + 0.006*"interactive" + 0.006*"super" + 0.006*"job" + 0.005*"building" + 0.005*"informative" + 0.005*"fantastic" + 0.005*"bonding" + 0.005*"roberto" + 0.004*"thomas" + 0.004*"lot" + 0.004*"perfect" + 0.004*"thank" + 0.004*"made" + 0.003*"company" + 0.003*"awesome" + 0.003*"people" + 0.003*"perspective" + 0.003*"recommended"
Topic 4: 0.062*"sharon" + 0.038*"thank" + 0.033*"much" + 0.031*"mark" + 0.024*"david" + 0.024*"experience" + 0.024*"enjoyed" + 0.021*"thanks" + 0.015*"time" + 0.015*"roberto" + 0.015*"ben" + 0.014*"great" + 0.014*"best" + 0.013*"see" + 0.012*"birthday" + 0.010*"really" + 0.010*"keshav" + 0.010*"glad" + 0.009*"happy" + 0.009*"family" + 0.008*"loved" + 0.008*"meeting" + 0.007*"hope" + 0.007*"soon" + 0.007*"lovely" + 0.006*"gift" + 0.006*"’" + 0.006*"session" + 0.006*"im" + 0.006*"kind" + 0.005*"meet" + 0.005*"fun" + 0.005*"wonderful" + 0.005*"review" + 0.005*"educational" + 0.005*"joining" + 0.005*"year" + 0.004*"future" + 0.004*"day" + 0.004*"old" + 0.004*"friends" + 0.004*"amazing" + 0.004*"pleasure" + 0.004*"lot" + 0.004*"one" + 0.004*"appreciate" + 0.003*"friend" + 0.003*"know" + 0.003*"please" + 0.003*"special"
Topic 5: 0.036*"experience" + 0.029*"great" + 0.026*"recommend" + 0.022*"highly" + 0.021*"fun" + 0.021*"learned" + 0.020*"lot" + 0.019*"knowledgeable" + 0.016*"interesting" + 0.015*"history" + 0.012*"new" + 0.012*"learning" + 0.011*"learn" + 0.010*"things" + 0.010*"’" + 0.010*"friendly" + 0.009*"way" + 0.009*"really" + 0.009*"would" + 0.009*"art" + 0.009*"informative" + 0.008*"class" + 0.008*"host" + 0.008*"recommended" + 0.008*"reading" + 0.008*"time" + 0.007*"anyone" + 0.007*"roberto" + 0.007*"information" + 0.007*"astrology" + 0.007*"engaging" + 0.007*"culture" + 0.006*"session" + 0.006*"prague" + 0.006*"super" + 0.006*"interested" + 0.006*"amazing" + 0.006*"chart" + 0.006*"excellent" + 0.005*"wonderful" + 0.005*"also" + 0.005*"insight" + 0.005*"loved" + 0.005*"questions" + 0.005*"definitely" + 0.004*"plague" + 0.004*"spot" + 0.004*"recipe" + 0.004*"subject" + 0.004*"topic"
Topic 6: 0.046*"experience" + 0.017*"us" + 0.016*"really" + 0.015*"made" + 0.015*"great" + 0.013*"recommend" + 0.011*"feel" + 0.010*"wonderful" + 0.009*"ireland" + 0.009*"would" + 0.008*"like" + 0.008*"cooking" + 0.008*"’" + 0.008*"amazing" + 0.007*"highly" + 0.007*"reading" + 0.007*"questions" + 0.007*"stories" + 0.007*"fun" + 0.007*"time" + 0.006*"well" + 0.006*"host" + 0.006*"felt" + 0.006*"life" + 0.006*"history" + 0.006*"also" + 0.006*"enjoyed" + 0.006*"knowledge" + 0.006*"friendly" + 0.005*"interesting" + 0.005*"even" + 0.005*"definitely" + 0.005*"astrology" + 0.004*"loved" + 0.004*"knowledgeable" + 0.004*"make" + 0.004*"everyone" + 0.004*"way" + 0.004*"tour" + 0.004*"gave" + 0.004*"sure" + 0.004*"art" + 0.003*"makes" + 0.003*"sense" + 0.003*"travel" + 0.003*"engaging" + 0.003*"insights" + 0.003*"personal" + 0.003*"excellent" + 0.003*"group"
Regularized KL Divergence: 0.13767184829164006

Coherence Score:  -4.605347897191561
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Number of Topics: 7
Regularized KL Divergence: 0.13344956859414556

Coherence Score:  -5.06843065550227
Number of Topics: 8
Regularized KL Divergence: 0.12989122990394986

Coherence Score:  -4.8345485809084305
Number of Topics: 9
Regularized KL Divergence: 0.11765021838325192

Coherence Score:  -3.934886203627453
Topic 1: 0.107*"sharon" + 0.059*"thank" + 0.058*"much" + 0.056*"enjoyed" + 0.053*"experience" + 0.038*"really" + 0.034*"great" + 0.019*"lot" + 0.017*"time" + 0.016*"learned" + 0.013*"fun" + 0.013*"thanks" + 0.012*"lovely" + 0.012*"glad" + 0.012*"see" + 0.010*"wonderful" + 0.010*"meeting" + 0.010*"knowledge" + 0.008*"amazing" + 0.008*"happy" + 0.008*"thoroughly" + 0.007*"story" + 0.007*"session" + 0.007*"joining" + 0.007*"nice" + 0.007*"host" + 0.006*"im" + 0.006*"know" + 0.006*"area" + 0.006*"interesting" + 0.005*"hour" + 0.005*"best" + 0.005*"family" + 0.005*"prague" + 0.005*"guided" + 0.004*"roberto" + 0.004*"well" + 0.004*"passion" + 0.004*"kind" + 0.004*"guys" + 0.004*"transported" + 0.004*"things" + 0.003*"plan" + 0.003*"nick" + 0.003*"loved" + 0.003*"readings" + 0.003*"plague" + 0.003*"sharing" + 0.003*"teller" + 0.003*"telling"
Topic 2: 0.042*"class" + 0.037*"art" + 0.017*"new" + 0.016*"wait" + 0.015*"insightful" + 0.012*"really" + 0.012*"learned" + 0.012*"make" + 0.012*"things" + 0.012*"cant" + 0.010*"great" + 0.010*"also" + 0.010*"reading" + 0.010*"learn" + 0.010*"experience" + 0.009*"life" + 0.009*"many" + 0.009*"taking" + 0.008*"knowledge" + 0.008*"visit" + 0.008*"cook" + 0.008*"past" + 0.008*"love" + 0.008*"future" + 0.008*"enjoyed" + 0.007*"chart" + 0.007*"take" + 0.007*"session" + 0.007*"lot" + 0.007*"us" + 0.006*"amazing" + 0.006*"aspects" + 0.006*"chef" + 0.006*"history" + 0.006*"learnt" + 0.006*"walk" + 0.005*"ask" + 0.005*"tacos" + 0.005*"im" + 0.005*"like" + 0.005*"learning" + 0.005*"tips" + 0.005*"able" + 0.005*"questions" + 0.004*"years" + 0.004*"wonderful" + 0.004*"use" + 0.004*"making" + 0.004*"city" + 0.004*"excellent"
Topic 3: 0.064*"’" + 0.022*"experience" + 0.018*"reading" + 0.011*"even" + 0.011*"one" + 0.011*"ireland" + 0.011*"know" + 0.009*"loved" + 0.009*"first" + 0.009*"better" + 0.009*"much" + 0.007*"family" + 0.007*"could" + 0.007*"gift" + 0.007*"online" + 0.006*"best" + 0.006*"present" + 0.006*"surprised" + 0.006*"expect" + 0.006*"time" + 0.006*"different" + 0.006*"past" + 0.006*"like" + 0.005*"say" + 0.005*"mexico" + 0.005*"turned" + 0.005*"birthday" + 0.005*"walking" + 0.005*"felt" + 0.005*"great" + 0.005*"done" + 0.005*"person" + 0.005*"get" + 0.005*"astrology" + 0.005*"love" + 0.005*"didnt" + 0.004*"something" + 0.004*"ever" + 0.004*"wonderful" + 0.004*"never" + 0.004*"fun" + 0.004*"able" + 0.004*"said" + 0.004*"see" + 0.004*"things" + 0.004*"experiences" + 0.004*"special" + 0.004*"another" + 0.004*"year" + 0.004*"update"
Topic 4: 0.037*"experience" + 0.035*"great" + 0.026*"us" + 0.022*"time" + 0.019*"beautiful" + 0.016*"wonderful" + 0.016*"made" + 0.015*"fun" + 0.015*"feel" + 0.012*"class" + 0.011*"way" + 0.009*"like" + 0.009*"stories" + 0.009*"make" + 0.008*"amazing" + 0.008*"making" + 0.008*"loved" + 0.007*"learning" + 0.006*"friendly" + 0.005*"first" + 0.005*"shared" + 0.005*"teacher" + 0.005*"life" + 0.005*"night" + 0.005*"fascinating" + 0.005*"also" + 0.005*"warm" + 0.005*"welcoming" + 0.004*"felt" + 0.004*"knowledge" + 0.004*"job" + 0.004*"comfortable" + 0.004*"world" + 0.004*"definitely" + 0.004*"home" + 0.004*"online" + 0.004*"new" + 0.004*"much" + 0.004*"took" + 0.004*"even" + 0.004*"family" + 0.004*"host" + 0.004*"things" + 0.004*"thorough" + 0.004*"makes" + 0.004*"gave" + 0.003*"away" + 0.003*"spend" + 0.003*"date" + 0.003*"truly"
Topic 5: 0.094*"mark" + 0.037*"ben" + 0.035*"thanks" + 0.030*"meditation" + 0.030*"thank" + 0.023*"hope" + 0.020*"soon" + 0.019*"much" + 0.019*"best" + 0.016*"day" + 0.016*"see" + 0.016*"meet" + 0.014*"visit" + 0.013*"future" + 0.012*"review" + 0.012*"person" + 0.011*"forward" + 0.010*"lovely" + 0.009*"perspective" + 0.009*"enjoyed" + 0.009*"happy" + 0.009*"please" + 0.009*"one" + 0.008*"great" + 0.008*"experience" + 0.008*"pleasure" + 0.007*"look" + 0.007*"glad" + 0.006*"hi" + 0.006*"words" + 0.006*"places" + 0.006*"appreciate" + 0.006*"feedback" + 0.006*"someday" + 0.006*"meeting" + 0.006*"kind" + 0.006*"always" + 0.006*"list" + 0.006*"safe" + 0.005*"google" + 0.005*"stay" + 0.005*"session" + 0.005*"comments" + 0.005*"looking" + 0.004*"share" + 0.004*"im" + 0.004*"coming" + 0.004*"clarity" + 0.004*"hear" + 0.004*"matter"
Topic 6: 0.047*"tour" + 0.029*"experience" + 0.019*"interesting" + 0.017*"history" + 0.016*"really" + 0.013*"questions" + 0.013*"us" + 0.013*"fun" + 0.013*"knowledgeable" + 0.013*"delicious" + 0.011*"guide" + 0.010*"life" + 0.010*"prague" + 0.010*"like" + 0.009*"culture" + 0.009*"made" + 0.008*"food" + 0.008*"travel" + 0.008*"informative" + 0.008*"street" + 0.008*"virtual" + 0.007*"city" + 0.007*"way" + 0.007*"would" + 0.007*"information" + 0.007*"definitely" + 0.007*"great" + 0.007*"well" + 0.006*"lot" + 0.006*"want" + 0.006*"learn" + 0.006*"host" + 0.006*"felt" + 0.006*"gave" + 0.006*"learned" + 0.006*"friendly" + 0.006*"go" + 0.006*"plague" + 0.006*"person" + 0.006*"nice" + 0.006*"visit" + 0.006*"recommend" + 0.005*"trip" + 0.005*"reading" + 0.005*"insights" + 0.005*"also" + 0.005*"facts" + 0.005*"wonderful" + 0.004*"streets" + 0.004*"feel"
Topic 7: 0.068*"experience" + 0.064*"recommend" + 0.050*"highly" + 0.029*"would" + 0.025*"great" + 0.015*"time" + 0.014*"amazing" + 0.013*"fun" + 0.013*"wonderful" + 0.012*"anyone" + 0.011*"everyone" + 0.011*"definitely" + 0.010*"host" + 0.010*"loved" + 0.010*"recommended" + 0.009*"made" + 0.009*"engaging" + 0.009*"family" + 0.009*"knowledgeable" + 0.008*"fantastic" + 0.008*"group" + 0.008*"absolutely" + 0.008*"us" + 0.007*"friends" + 0.007*"birthday" + 0.006*"friendly" + 0.006*"session" + 0.006*"virtual" + 0.006*"engaged" + 0.005*"informative" + 0.005*"booked" + 0.005*"excellent" + 0.005*"really" + 0.005*"job" + 0.005*"sure" + 0.004*"interactive" + 0.004*"astrology" + 0.004*"wishes" + 0.004*"questions" + 0.004*"storyteller" + 0.004*"team" + 0.004*"funny" + 0.004*"thoughtful" + 0.004*"interested" + 0.004*"incredible" + 0.003*"answered" + 0.003*"knowledgable" + 0.003*"educational" + 0.003*"special" + 0.003*"gift"
Topic 8: 0.030*"david" + 0.029*"great" + 0.020*"accurate" + 0.019*"experience" + 0.018*"easy" + 0.017*"well" + 0.014*"follow" + 0.013*"really" + 0.013*"astrology" + 0.011*"good" + 0.011*"time" + 0.010*"drawing" + 0.010*"also" + 0.009*"clear" + 0.009*"everything" + 0.009*"instructions" + 0.008*"reading" + 0.007*"nice" + 0.007*"video" + 0.007*"explained" + 0.006*"western" + 0.006*"make" + 0.006*"place" + 0.006*"thomas" + 0.006*"understand" + 0.006*"sense" + 0.006*"sure" + 0.006*"session" + 0.006*"fun" + 0.006*"super" + 0.005*"clearly" + 0.005*"presentation" + 0.005*"job" + 0.005*"along" + 0.005*"understanding" + 0.005*"engaging" + 0.004*"curious" + 0.004*"us" + 0.004*"lot" + 0.004*"following" + 0.004*"tell" + 0.004*"explain" + 0.004*"humor" + 0.004*"explaining" + 0.004*"extremely" + 0.004*"techniques" + 0.004*"level" + 0.004*"steps" + 0.004*"questions" + 0.004*"host"
Topic 9: 0.054*"great" + 0.053*"team" + 0.049*"fun" + 0.030*"event" + 0.030*"experience" + 0.027*"cooking" + 0.021*"activity" + 0.020*"time" + 0.019*"group" + 0.018*"work" + 0.013*"really" + 0.012*"virtual" + 0.011*"way" + 0.011*"italy" + 0.011*"together" + 0.011*"everyone" + 0.010*"engaging" + 0.009*"host" + 0.009*"super" + 0.008*"lot" + 0.008*"building" + 0.008*"would" + 0.008*"recommend" + 0.007*"bonding" + 0.007*"much" + 0.006*"booked" + 0.006*"loved" + 0.006*"definitely" + 0.006*"different" + 0.006*"lots" + 0.005*"specific" + 0.005*"enjoyed" + 0.005*"people" + 0.005*"good" + 0.004*"family" + 0.004*"meal" + 0.004*"get" + 0.004*"interactive" + 0.004*"perfect" + 0.004*"friends" + 0.004*"something" + 0.004*"company" + 0.004*"made" + 0.004*"parts" + 0.004*"amazing" + 0.004*"japanese" + 0.004*"job" + 0.004*"well" + 0.004*"us" + 0.004*"calm"
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Number of Topics: 10
Regularized KL Divergence: 0.11866277923285111

Coherence Score:  -5.051941802693543
Number of Topics: 11
Regularized KL Divergence: 0.11135830295449993

Coherence Score:  -4.478044448372807
Number of Topics: 12
Topic 1: 0.067*"cooking" + 0.048*"enjoyed" + 0.037*"ben" + 0.036*"delicious" + 0.032*"im" + 0.031*"thank" + 0.030*"glad" + 0.029*"experience" + 0.026*"much" + 0.026*"really" + 0.019*"knowledge" + 0.018*"liked" + 0.015*"joining" + 0.014*"thanks" + 0.011*"meal" + 0.010*"wan" + 0.010*"cook" + 0.010*"david" + 0.009*"appreciate" + 0.009*"best" + 0.008*"time" + 0.008*"recipe" + 0.008*"guys" + 0.008*"come" + 0.008*"daily" + 0.007*"make" + 0.007*"clarity" + 0.007*"situation" + 0.006*"style" + 0.006*"back" + 0.006*"someday" + 0.006*"happy" + 0.006*"session" + 0.006*"great" + 0.005*"result" + 0.005*"traditional" + 0.005*"chef" + 0.005*"willing" + 0.005*"review" + 0.004*"turned" + 0.004*"precise" + 0.004*"always" + 0.004*"hi" + 0.004*"whats" + 0.004*"lovely" + 0.004*"complete" + 0.004*"dish" + 0.004*"cooked" + 0.004*"deep" + 0.004*"sometime"
Topic 2: 0.070*"recommend" + 0.063*"experience" + 0.056*"highly" + 0.032*"great" + 0.031*"would" + 0.029*"fun" + 0.015*"informative" + 0.015*"time" + 0.015*"knowledgeable" + 0.013*"definitely" + 0.012*"recommended" + 0.010*"engaging" + 0.010*"amazing" + 0.010*"anyone" + 0.010*"host" + 0.009*"everyone" + 0.009*"wonderful" + 0.009*"virtual" + 0.009*"group" + 0.009*"team" + 0.008*"loved" + 0.008*"knowledge" + 0.008*"much" + 0.008*"interactive" + 0.008*"event" + 0.007*"guide" + 0.007*"really" + 0.007*"super" + 0.007*"learned" + 0.007*"lot" + 0.006*"family" + 0.006*"fantastic" + 0.006*"excellent" + 0.005*"friendly" + 0.005*"enjoyed" + 0.005*"interesting" + 0.005*"made" + 0.005*"detailed" + 0.005*"friends" + 0.005*"learning" + 0.005*"extremely" + 0.004*"entertaining" + 0.004*"booked" + 0.004*"knowledgable" + 0.004*"absolutely" + 0.004*"personable" + 0.004*"session" + 0.004*"fascinating" + 0.004*"educational" + 0.004*"“"
Topic 3: 0.055*"team" + 0.050*"great" + 0.038*"fun" + 0.033*"experience" + 0.024*"activity" + 0.023*"event" + 0.020*"time" + 0.019*"work" + 0.017*"together" + 0.017*"way" + 0.017*"virtual" + 0.014*"really" + 0.011*"walking" + 0.011*"us" + 0.010*"group" + 0.010*"step" + 0.009*"building" + 0.009*"western" + 0.009*"everyone" + 0.008*"loved" + 0.008*"family" + 0.007*"enjoyed" + 0.007*"bonding" + 0.007*"different" + 0.007*"get" + 0.006*"making" + 0.006*"booked" + 0.006*"much" + 0.006*"people" + 0.006*"friends" + 0.005*"something" + 0.005*"connect" + 0.005*"job" + 0.005*"creative" + 0.005*"perfect" + 0.005*"wonderful" + 0.005*"good" + 0.004*"host" + 0.004*"lot" + 0.004*"made" + 0.004*"amazing" + 0.004*"shes" + 0.004*"virtually" + 0.004*"nice" + 0.004*"delicious" + 0.004*"energy" + 0.004*"scratch" + 0.004*"turned" + 0.003*"even" + 0.003*"engaging"
Topic 4: 0.086*"’" + 0.034*"city" + 0.025*"one" + 0.025*"visit" + 0.023*"experience" + 0.022*"person" + 0.016*"wait" + 0.016*"time" + 0.015*"best" + 0.013*"us" + 0.013*"trip" + 0.013*"go" + 0.012*"love" + 0.011*"next" + 0.010*"forward" + 0.010*"want" + 0.010*"amazing" + 0.010*"ever" + 0.010*"day" + 0.009*"real" + 0.008*"hour" + 0.008*"walk" + 0.008*"even" + 0.008*"never" + 0.007*"experiences" + 0.007*"looking" + 0.007*"look" + 0.007*"year" + 0.007*"book" + 0.006*"second" + 0.006*"done" + 0.006*"cant" + 0.006*"class" + 0.006*"actually" + 0.006*"virtual" + 0.006*"made" + 0.006*"though" + 0.005*"online" + 0.005*"able" + 0.005*"future" + 0.005*"airbnb" + 0.005*"another" + 0.005*"take" + 0.005*"really" + 0.005*"see" + 0.005*"today" + 0.005*"first" + 0.005*"much" + 0.005*"old" + 0.004*"traveling"
Topic 5: 0.078*"tour" + 0.040*"experience" + 0.033*"great" + 0.031*"really" + 0.022*"stories" + 0.021*"enjoyed" + 0.021*"history" + 0.019*"interesting" + 0.017*"food" + 0.015*"accurate" + 0.013*"amazing" + 0.013*"questions" + 0.012*"wonderful" + 0.012*"reading" + 0.011*"life" + 0.011*"host" + 0.010*"us" + 0.010*"fantastic" + 0.009*"made" + 0.009*"presentation" + 0.009*"engaging" + 0.009*"loved" + 0.008*"friendly" + 0.008*"session" + 0.008*"answered" + 0.008*"also" + 0.008*"virtual" + 0.008*"warm" + 0.007*"comfortable" + 0.007*"learning" + 0.006*"video" + 0.006*"subject" + 0.006*"personal" + 0.006*"story" + 0.006*"learned" + 0.006*"told" + 0.005*"passionate" + 0.005*"time" + 0.005*"information" + 0.005*"storyteller" + 0.005*"feel" + 0.005*"nice" + 0.005*"thoroughly" + 0.005*"makes" + 0.005*"shared" + 0.005*"absolutely" + 0.005*"passion" + 0.005*"fun" + 0.005*"details" + 0.005*"storytelling"
Topic 6: 0.037*"reading" + 0.037*"art" + 0.035*"david" + 0.025*"us" + 0.021*"tour" + 0.019*"birthday" + 0.018*"loved" + 0.018*"experience" + 0.015*"gift" + 0.012*"family" + 0.011*"great" + 0.010*"insights" + 0.009*"time" + 0.009*"special" + 0.009*"drawing" + 0.008*"really" + 0.008*"session" + 0.008*"friends" + 0.007*"also" + 0.007*"wonderful" + 0.006*"made" + 0.006*"even" + 0.006*"gave" + 0.006*"said" + 0.006*"friend" + 0.005*"night" + 0.005*"please" + 0.005*"private" + 0.005*"years" + 0.005*"well" + 0.005*"insight" + 0.005*"daughter" + 0.005*"booked" + 0.005*"amazing" + 0.005*"husband" + 0.005*"make" + 0.005*"video" + 0.005*"bought" + 0.005*"meeting" + 0.004*"class" + 0.004*"got" + 0.004*"mom" + 0.004*"making" + 0.004*"able" + 0.004*"parents" + 0.004*"date" + 0.003*"take" + 0.003*"celebrate" + 0.003*"zoom" + 0.003*"around"
Topic 7: 0.038*"class" + 0.024*"experience" + 0.024*"great" + 0.023*"easy" + 0.019*"fun" + 0.018*"really" + 0.016*"learned" + 0.016*"make" + 0.015*"lot" + 0.014*"things" + 0.014*"new" + 0.013*"follow" + 0.012*"made" + 0.012*"us" + 0.012*"insightful" + 0.012*"also" + 0.011*"delicious" + 0.011*"learn" + 0.011*"well" + 0.009*"italy" + 0.008*"clear" + 0.008*"good" + 0.008*"instructions" + 0.007*"along" + 0.007*"understand" + 0.007*"time" + 0.006*"learning" + 0.006*"informative" + 0.006*"way" + 0.006*"super" + 0.006*"explained" + 0.006*"something" + 0.006*"patient" + 0.005*"gave" + 0.005*"sense" + 0.005*"explaining" + 0.005*"friendly" + 0.005*"enjoyed" + 0.005*"taking" + 0.005*"amazing" + 0.005*"able" + 0.005*"definitely" + 0.005*"guidance" + 0.005*"making" + 0.005*"interesting" + 0.005*"session" + 0.005*"loved" + 0.005*"tacos" + 0.005*"fascinating" + 0.005*"never"
Topic 8: 0.058*"thanks" + 0.052*"street" + 0.021*"ben" + 0.021*"meeting" + 0.020*"best" + 0.020*"much" + 0.019*"meet" + 0.019*"great" + 0.018*"detail" + 0.017*"lovely" + 0.017*"thomas" + 0.016*"day" + 0.014*"review" + 0.013*"feedback" + 0.013*"buenos" + 0.013*"aires" + 0.012*"visit" + 0.012*"enjoyed" + 0.012*"kind" + 0.011*"experience" + 0.011*"hope" + 0.011*"know" + 0.011*"places" + 0.010*"words" + 0.009*"look" + 0.009*"comments" + 0.009*"glad" + 0.009*"person" + 0.009*"future" + 0.008*"safe" + 0.008*"back" + 0.008*"also" + 0.008*"saw" + 0.008*"wish" + 0.007*"forward" + 0.007*"time" + 0.007*"cultural" + 0.007*"stay" + 0.007*"im" + 0.006*"visiting" + 0.006*"coming" + 0.006*"session" + 0.006*"nick" + 0.006*"valuable" + 0.006*"nice" + 0.005*"hi" + 0.005*"depth" + 0.005*"relaxing" + 0.005*"useful" + 0.005*"accessible"
Topic 9: 0.026*"beautiful" + 0.023*"travel" + 0.023*"experience" + 0.017*"interesting" + 0.015*"great" + 0.014*"fun" + 0.012*"way" + 0.012*"facts" + 0.012*"guide" + 0.011*"many" + 0.011*"things" + 0.010*"knowledgeable" + 0.010*"learn" + 0.009*"past" + 0.009*"time" + 0.009*"information" + 0.009*"able" + 0.008*"lot" + 0.008*"wishes" + 0.008*"new" + 0.008*"spot" + 0.008*"get" + 0.008*"future" + 0.007*"life" + 0.007*"prague" + 0.007*"historical" + 0.006*"gave" + 0.006*"know" + 0.006*"different" + 0.006*"see" + 0.006*"could" + 0.006*"learned" + 0.006*"really" + 0.006*"times" + 0.006*"aspects" + 0.006*"us" + 0.005*"wonderful" + 0.005*"tips" + 0.005*"topic" + 0.005*"area" + 0.005*"also" + 0.005*"gives" + 0.005*"lots" + 0.005*"current" + 0.005*"little" + 0.005*"visit" + 0.005*"want" + 0.004*"pictures" + 0.004*"give" + 0.004*"present"
Topic 10: 0.142*"thank" + 0.082*"much" + 0.051*"culture" + 0.041*"see" + 0.034*"soon" + 0.027*"time" + 0.026*"happy" + 0.024*"great" + 0.023*"way" + 0.020*"spend" + 0.017*"hope" + 0.015*"experience" + 0.014*"fun" + 0.013*"wonderful" + 0.013*"pleasure" + 0.012*"learned" + 0.011*"hour" + 0.011*"nice" + 0.011*"lot" + 0.011*"best" + 0.010*"enjoyed" + 0.010*"local" + 0.009*"family" + 0.009*"evening" + 0.008*"thanks" + 0.008*"share" + 0.007*"content" + 0.007*"always" + 0.007*"lovely" + 0.007*"another" + 0.006*"love" + 0.006*"japan" + 0.005*"afternoon" + 0.005*"new" + 0.005*"guests" + 0.005*"meet" + 0.005*"boyfriend" + 0.005*"friends" + 0.004*"gracias" + 0.004*"plus" + 0.004*"future" + 0.004*"kind" + 0.004*"dear" + 0.004*"hello" + 0.004*"forward" + 0.004*"one" + 0.004*"inside" + 0.004*"remember" + 0.003*"hoping" + 0.003*"active"
Topic 11: 0.050*"great" + 0.038*"questions" + 0.032*"well" + 0.028*"fun" + 0.024*"host" + 0.022*"group" + 0.021*"experience" + 0.020*"us" + 0.019*"time" + 0.018*"job" + 0.017*"engaging" + 0.017*"answer" + 0.016*"knowledgeable" + 0.013*"helpful" + 0.012*"friendly" + 0.012*"good" + 0.012*"super" + 0.011*"everyone" + 0.010*"excellent" + 0.010*"engaged" + 0.009*"really" + 0.009*"lot" + 0.009*"knowledge" + 0.008*"event" + 0.008*"worth" + 0.008*"explain" + 0.008*"sure" + 0.008*"prepared" + 0.007*"know" + 0.006*"kept" + 0.006*"personable" + 0.006*"steps" + 0.006*"organized" + 0.006*"value" + 0.006*"everything" + 0.006*"kind" + 0.005*"enthusiastic" + 0.005*"definitely" + 0.005*"made" + 0.005*"giving" + 0.005*"overall" + 0.005*"didnt" + 0.005*"google" + 0.005*"throughout" + 0.005*"interesting" + 0.004*"participants" + 0.004*"funny" + 0.004*"explained" + 0.004*"quizzes" + 0.004*"went"
Topic 12: 0.073*"experience" + 0.070*"sharon" + 0.032*"like" + 0.027*"recommend" + 0.023*"would" + 0.023*"felt" + 0.023*"feel" + 0.019*"history" + 0.019*"made" + 0.017*"wonderful" + 0.015*"meditation" + 0.013*"first" + 0.013*"life" + 0.011*"online" + 0.011*"definitely" + 0.010*"highly" + 0.010*"really" + 0.009*"time" + 0.009*"unique" + 0.009*"great" + 0.008*"know" + 0.008*"anyone" + 0.008*"questions" + 0.008*"sure" + 0.007*"make" + 0.007*"better" + 0.007*"lovely" + 0.006*"ask" + 0.006*"us" + 0.006*"amazing" + 0.006*"kind" + 0.006*"nice" + 0.006*"interested" + 0.005*"home" + 0.005*"following" + 0.005*"get" + 0.005*"knowledgeable" + 0.005*"even" + 0.005*"way" + 0.005*"much" + 0.005*"love" + 0.005*"’" + 0.005*"truly" + 0.005*"world" + 0.005*"hosts" + 0.005*"sweet" + 0.005*"could" + 0.005*"person" + 0.004*"special" + 0.004*"guide"
Regularized KL Divergence: 0.10574929577323978

Coherence Score:  -4.395426791412482
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Number of Topics: 13
Regularized KL Divergence: 0.10221481458071863

Coherence Score:  -4.101138975541551
Number of Topics: 14
Regularized KL Divergence: 0.09686472983529537

Coherence Score:  -4.290367000564225
Number of Topics: 15
Regularized KL Divergence: 0.09488371446229986

Coherence Score:  -4.0580439780182145
Number of Topics: 16
Regularized KL Divergence: 0.09084777657703312

Coherence Score:  -4.173337513596503
Number of Topics: 17
Regularized KL Divergence: 0.08892484977252381

Coherence Score:  -4.23478470063094
Number of Topics: 18
Regularized KL Divergence: 0.08557603700943157

Coherence Score:  -4.4199345610182394
Number of Topics: 19
Regularized KL Divergence: 0.0812576896307415

Coherence Score:  -4.544099080848863
Number of Topics: 20
Regularized KL Divergence: 0.07908468462059379

Coherence Score:  -4.372528270833375
Number of Topics: 21
Regularized KL Divergence: 0.07887816095935046

Coherence Score:  -4.64196687501812
Number of Topics: 22
Regularized KL Divergence: 0.07441731695768586

Coherence Score:  -4.885433875697085
Number of Topics: 23
Regularized KL Divergence: 0.07168886353414157

Coherence Score:  -4.408400442651161
Number of Topics: 24
Regularized KL Divergence: 0.07069066398072452

Coherence Score:  -4.6169521371015
Number of Topics: 25
Regularized KL Divergence: 0.06886776142299451

Coherence Score:  -4.584731630336083
Number of Topics: 26
Regularized KL Divergence: 0.0669016775866863

Coherence Score:  -4.893260962676819
Number of Topics: 27
Regularized KL Divergence: 0.0651387758128705

Coherence Score:  -4.936310123554681
Number of Topics: 28
Regularized KL Divergence: 0.06317656879111015

Coherence Score:  -4.785031338722814
Number of Topics: 29
Regularized KL Divergence: 0.060434108905713844

Coherence Score:  -5.118475963032963
Number of Topics: 30
Regularized KL Divergence: 0.05978567048305021

Coherence Score:  -4.900424414746465
Number of Topics: 31
Regularized KL Divergence: 0.05790966987669195

Coherence Score:  -4.9277638785415006
Number of Topics: 32
Regularized KL Divergence: 0.0569883934665267

Coherence Score:  -4.917362481893923
Number of Topics: 33
Regularized KL Divergence: 0.05565212752274421

Coherence Score:  -4.907238439458415
Number of Topics: 34
Regularized KL Divergence: 0.05519733579480683

Coherence Score:  -5.353847710135383
Number of Topics: 35
Regularized KL Divergence: 0.05409626092652503

Coherence Score:  -5.889360707344037
Number of Topics: 36
Regularized KL Divergence: 0.051912630805552806

Coherence Score:  -5.278443364377891
Number of Topics: 37
Regularized KL Divergence: 0.051241812657729285

Coherence Score:  -5.432364281071087
Number of Topics: 38
Regularized KL Divergence: 0.05072886854172923

Coherence Score:  -5.295738787412598
Number of Topics: 39
Regularized KL Divergence: 0.04972949210054025

Coherence Score:  -5.704771159601427
Number of Topics: 40
Regularized KL Divergence: 0.048895980335087214

Coherence Score:  -5.451860203393424
Number of Topics: 41
Regularized KL Divergence: 0.04765952089330277

Coherence Score:  -5.797095039294668
Number of Topics: 42
Regularized KL Divergence: 0.04718592343973033

Coherence Score:  -5.632555738888251
Number of Topics: 43
Regularized KL Divergence: 0.046136336365824634

Coherence Score:  -5.789355288517998
Number of Topics: 44
Regularized KL Divergence: 0.04557680904353518

Coherence Score:  -5.818863762839254
Number of Topics: 45
Regularized KL Divergence: 0.04403657213350202

Coherence Score:  -5.500912260601135
Number of Topics: 46
Regularized KL Divergence: 0.043795645005226216

Coherence Score:  -5.5112609141839615
Number of Topics: 47
Regularized KL Divergence: 0.04270433456085062

Coherence Score:  -5.526733769151996
Number of Topics: 48
Regularized KL Divergence: 0.04283167723511578

Coherence Score:  -5.619585428479463
Number of Topics: 49
Regularized KL Divergence: 0.04174051448969829

Coherence Score:  -5.7473267159153565
Number of Topics: 50
Regularized KL Divergence: 0.04082176374783531

Coherence Score:  -5.4687403428682435
Number of Topics: 51
Regularized KL Divergence: 0.04034914946621729

Coherence Score:  -6.018964883500464
Number of Topics: 52
Regularized KL Divergence: 0.04004967521957779

Coherence Score:  -6.103843488733398
Number of Topics: 53
Regularized KL Divergence: 0.03929844007485237

Coherence Score:  -5.958839904284072
Number of Topics: 54
Regularized KL Divergence: 0.03881982436746807

Coherence Score:  -6.039389243896687
Number of Topics: 55
Regularized KL Divergence: 0.038684064429627976

Coherence Score:  -6.1026834961396546
Number of Topics: 56
Regularized KL Divergence: 0.037840002302230565

Coherence Score:  -6.371804824866706
Number of Topics: 57
Regularized KL Divergence: 0.03719382890156849

Coherence Score:  -6.2964153690076765
Number of Topics: 58
Regularized KL Divergence: 0.036693637110918206

Coherence Score:  -6.146162163988871
Number of Topics: 59
Regularized KL Divergence: 0.035975843033180285

Coherence Score:  -5.938094346724011
Number of Topics: 60
Regularized KL Divergence: 0.03663976341621169

Coherence Score:  -6.021594687194225
Dictionary successfully converted to CSV file: Final_RD_Coherence.csv
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